ICDAR 2021 Competition on Scene Video Text Spotting
- URL: http://arxiv.org/abs/2107.11919v1
- Date: Mon, 26 Jul 2021 01:25:57 GMT
- Title: ICDAR 2021 Competition on Scene Video Text Spotting
- Authors: Zhanzhan Cheng, Jing Lu, Baorui Zou, Shuigeng Zhou, and Fei Wu
- Abstract summary: Scene video text spotting (SVTS) is a very important research topic because of many real-life applications.
This paper includes dataset descriptions, task definitions, evaluation protocols and results summaries of the ICDAR 2021 on SVTS competition.
- Score: 28.439390836950025
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: Scene video text spotting (SVTS) is a very important research topic because
of many real-life applications. However, only a little effort has put to
spotting scene video text, in contrast to massive studies of scene text
spotting in static images. Due to various environmental interferences like
motion blur, spotting scene video text becomes very challenging. To promote
this research area, this competition introduces a new challenge dataset
containing 129 video clips from 21 natural scenarios in full annotations. The
competition containts three tasks, that is, video text detection (Task 1),
video text tracking (Task 2) and end-to-end video text spotting (Task3). During
the competition period (opened on 1st March, 2021 and closed on 11th April,
2021), a total of 24 teams participated in the three proposed tasks with 46
valid submissions, respectively. This paper includes dataset descriptions, task
definitions, evaluation protocols and results summaries of the ICDAR 2021 on
SVTS competition. Thanks to the healthy number of teams as well as submissions,
we consider that the SVTS competition has been successfully held, drawing much
attention from the community and promoting the field research and its
development.
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